SAIC: an iterative clustering approach for analysis of single cell RNA-seq data

被引:0
作者
Lu Yang
Jiancheng Liu
Qiang Lu
Arthur D. Riggs
Xiwei Wu
机构
[1] City of Hope,Integrative Genomics Core, Beckman Research Institute
[2] City of Hope,Department of Developmental and Stem Cell Biology, Beckman Research Institute
[3] City of Hope,Diabetes and Metabolism Research Institute
[4] City of Hope,Department of Molecular and Cellular Biology, Beckman Research Institute
来源
BMC Genomics | / 18卷
关键词
Single cell; RNA-seq; Clustering; K-means; ANOVA; PCA; Signature genes; T-SNE;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 125 条
[1]  
Buganim Y(2012)Single-cell expression analyses during cellular reprogramming reveal an early stochastic and a late hierarchic phase Cell 150 1209-1222
[2]  
Faddah DA(2015)Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells Nat Biotechnol 33 155-160
[3]  
Cheng AW(2004)Bacterial persistence as a phenotypic switch Science 305 1622-1625
[4]  
Itskovich E(2007)Dissecting timing variability in yeast meiosis Cell 131 544-556
[5]  
Markoulaki S(2008)Variability and robustness in T cell activation from regulated heterogeneity in protein levels Science 321 1081-1084
[6]  
Ganz K(2014)Quantitative assessment of single-cell RNA-sequencing methods Nat Methods 11 41-46
[7]  
Klemm SL(2014)Validation of noise models for single-cell transcriptomics Nat Methods 11 637-640
[8]  
van Oudenaarden A(2015)Identification of cell types from single-cell transcriptomes using a novel clustering method Bioinformatics 31 1974-1980
[9]  
Jaenisch R(2015)Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq Science 347 1138-1142
[10]  
Buettner F(2014)Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape Proc Natl Acad Sci U S A 111 E5643-E5650